System and method for banking market analysis

ABSTRACT

Methods of estimating a fee earned by one or more advisors from various types of investment banking deals and transactions are disclosed. The deals or transactions may be a merger or acquisition, an initial public offering, an offering of convertible securities, a secondary offering, a block trade of securities, an offering of investment-grade debt securities and/or an offering of high-yield securities. The advisors may be investment banks performing on the roles of the various tiers of a syndicate, such as book runner, lead manager, co-lead manager, or co-manager. The method comprises retrieving data regarding the financial deal or deals of interest. The data may include an identification of the one or more advisors, the role of those advisors, and a parameter of the deal, such as the size of the deal, the geographic region for the deal, or the maturity date when the deal involves the issuance of debt securities.

BACKGROUND

The present invention generally concerns investment banking deals andtransactions and, more particularly, estimating fees for advisors forsuch deals and transactions.

Investment banks perform a variety of services for their clients. Onecommon role that investment banks assume is to help companies andgovernments issue securities, such as equity securities (e.g., stocks)or debt securities (e.g., bonds). Further, a number of investment banksmay act together as a “syndicate” to jointly assist in issuing thesecurities. Each investment bank that is part of the syndicate mayperform a different role or share a particular role with otherinvestment banks. The fee an investment bank earns from a deal typicallydepends on its role in the deal and the size of the deal.

The different advisory roles in a syndicate that an investment bank mayassume for a particular deal involving the issue of new securitiestypically include the book runner, the lead manager, the co-lead managerand the co-manager. The book runner typically acts as the managingunderwriter for the new issue. In that regard, the book runner typicallymaintains the book of securities sold. Also, the book runner isprimarily responsible for marketing the new issue to prospective buyers.The lead manager comprises the second tier of the syndication. Theresponsibilities of the lead manager are similar to the book runner, butto a lesser degree. The co-lead manager shares the lead managingresponsibilities with the lead manager, but to a lesser degree. Finally,the co-managers have the least management responsibility in a deal.Also, one or more investment banks may share the same role. That is, forexample, a particular deal may have two book runners. Typically, thebook runners receive the highest fee from a deal, followed by the leadmanager, then the co-lead manager(s), and then the co-manager(s).

Another service that investment bankers often perform is to act as anadvisor on mergers and acquisitions (M&As). A particular merger oracquisition deal may have one or a number of advisors. If there is oneadvisor, that sole advisor earns the entire fee for the deal. If thereare multiple advisors, those advisors split the fee.

SUMMARY

In one general aspect, the present invention is directed to a method ofestimating a fee earned by one or more advisors from an investmentbanking deal. The investment banking deal may be, for example, a mergeror acquisition, an initial public offering, an offering of convertiblesecurities, a secondary offering, a block trade of securities, anoffering of investment-grade debt securities and/or an offering ofhigh-yield securities. The advisors may be, for example, investmentbanks performing one of the roles of the various tiers of a syndicate,such as book runner, lead manager, co-lead manager, or co-manager forfinancing deals, or advisors for merger & acquisition deals.

According to various embodiments, the method includes retrieving dataregarding the investment banking deal or deals of interest. The data mayinclude an identification of the one or more advisors, the role of theone or more advisors, and a parameter of the deal, such as the size ofthe deal, the geographic region or country for the deal, and the creditrating and/or the maturity date when the deal involves the issuance ofdebt securities. The method further includes determining a fee estimatefor each of the one or more advisors based on a look-up table thatincludes a fee estimate based on the parameter of the deal and the roleof the advisor.

In various implementations, the method may further comprise retrievingdata regarding a plurality of such deals and determining the feeestimate for each of the one or more advisors for each of the pluralityof offerings, and then aggregating the fee estimates by product, byclient, by sector and/or and by region to determine market trendinformation.

In another general respect, embodiments of the present invention aredirected to a method of displaying market trend information in theinvestment banking industry. According to various embodiments, themethod comprises, for each of at least two investment banks, plotting amarker at a coordinate on a grid including two dimensions. A first axisof the grid may correspond to the wallet share of the investment bankover a period of time, and a second axis may correspond to the number ofclients serviced by the investment bank over the period of time. Inaddition, a parameter of each marker (such as the radius of a circlewhen the marker is a circle) may be related to the wallet of theassociated investment bank over the time period.

DESCRIPTION OF THE FIGURES

Embodiments of the present invention will be described by way of examplein conjunction with the following figures, wherein:

FIG. 1 is a diagram of a system according to various embodiments of thepresent invention;

FIG. 2 is a flowchart of a process flow through the M&A fee calculationmodule of the system of FIG. 1 according to various embodiments of thepresent invention;

FIG. 3 is a sample fee look-up table for the M&A fee calculation modulefor a region or country;

FIG. 4 is a sample chart of aggregated fee information for M&Atransactions;

FIG. 5 is a flowchart of a process flow through the equity products feecalculation module of the system of FIG. 1 according to variousembodiments of the present invention;

FIG. 6 is a sample fee look-up table for the equity products feecalculation module;

FIG. 7 is a sample chart of aggregated fee information for an equityproduct deal;

FIG. 8 is a flowchart of a process flow through the investment-gradedebt fee calculation module of the system of FIG. 1 according to variousembodiments of the present invention;

FIGS. 9 and 10 are sample fee look-up tables for the investment-gradedebt fee calculation module;

FIG. 11 is a flowchart of a process flow through the high yield feecalculation module of the system of FIG. 1 according to variousembodiments of the present invention;

FIGS. 12 and 13 are sample fee look-up tables for the high yield feecalculation module; and

FIG. 14 is a diagram of a two-dimensional grid for displaying markettrend information according to various embodiments of the presentinvention.

DESCRIPTION

FIG. 1 is a diagram of a system 10 for estimating fees and analyzingmarket trends in the investment banking industry. The system 10 includesa computing device 12 in communication with one or more databases 14 andone or more output devices, such as a printer 16 or a monitor 17. Thesystem 10 may also include data input devices, such as a keyboard 18 anda mouse 19, that permit a user of the system 10 to input data orprograms. Also, a user may be remotely located from the system 10, inwhich case user instructions and data may be communicated to the system10 via any type of suitable network communication technique or protocol.

The computing device 12 may include, as illustrated in FIG. 1, an M&Afee calculation module 20, an equity products fee calculation module 22,an investment-grade debt fee calculation module 24, a high yield feecalculation module 26, and a wallet share determination module 28. Themodules 20-28 may be implemented as software code to be executed by aprocessor (not shown) of the computing device 12 using any suitablecomputer language, such as, for example, SAS, Java, C, C++, or Perlusing, for example, conventional or object-oriented techniques. Thesoftware code may be stored as a series of instructions or commands on acomputer-readable medium, such as a random access memory (RAM), aread-only memory (ROM), a magnetic medium such as a hard drive or afloppy disk, or an optical medium, such as a CD-ROM. The computingdevice 12 may be implemented as one or a number of networked computingdevices, such as personal computers, laptops, workstations, servers,etc. The database(s) 14 may contain data regarding investment bankingdeals, as described in more detail below. Output from the modules 20-26may be communicated to the output devices for display.

The M&A fee calculation module 20 may estimate the fees earned byinvestment banks in advisor roles for M&A deals based on informationabout M&A deals stored in the database 14. The M&A deal data may includethe investment banks involved in the deal, the location (e.g., country)of the deal, the number of advisors and the size of the deal. Such datais available, for example, from Thomson Financial. From thisinformation, the M&A fee calculation module 20, as explained below, mayestimate the fee earned by each investment bank involved in the deal asan advisor. This analysis can be applied or the data can be aggregatedto detect and analyze trends in the investment banking industry. Theequity products fee calculation module 22 may do the same forequity-related product deals. Such equity-related product deals include,for example, initial public offerings (IPOs), secondary offerings,convertible security offerings and block trades of equity securities.Accordingly, the equity products fee calculation module 22 may estimatethe fees earned by the investment banks performing roles in the varioustiers (e.g., book runner, lead manager, co-lead manager, co-manager) ofa syndicate for such deals. The investment-grade debt fee calculationmodule 24 may do the same for investment-grade debt deals and the highyield fee calculation module 26 may do the same for offerings ofhigh-yield securities. The wallet share determination module 28 maydetermine wallet share-related information for advisors on such deals,such as investment banks, based on the fee data estimated by the module20-26. The term “wallet share” in this sense refers to an advisor's(such as an investment bank's) percentage of street business from aproduct, a client, a sector, a region or country, etc. The wallet sharedetermination module 28 may additionally aggregate and display suchwallet share-related information.

FIG. 2 is a flowchart of the process flow through the M&A feecalculation module 20 according to various embodiments of the presentinvention. The process starts at step 30, where M&A deal information isretrieved from the database 14. As mentioned above, the M&A dealinformation may include, for example, the region or country of the deal(e.g., North America, Europe, Latin America, Asia, Germany, etc.), thesize of the deal and the number of advisors. Next, at step 32, the M&Afee calculation module 20 may sort the deal data by deal region orcountry. Next, at step 34, the M&A fee calculation module 20 may sortthe deal data by deal size. For example, the M&A fee calculation module20 may sort the deal into a number of “buckets” grouped by deal size.For example, the M&A fee calculation module 20 may group deals into thefollowing buckets:

Bucket 1 $100 M-$500 M Bucket 2 $500 M-$1 B Bucket 3   $1 B-$5 B Bucket4   $5 B-$10 B Bucket 5   $10 B-$25 B Bucket 6 >$25 B

Next, at step 36, the M&A fee calculation module 20 may sort the databased on the number of advisors for the M&A transaction. M&Atransactions typically have a sole advisor or a number of advisors.Then, at step 38, the M&A fee calculation module 20 may estimate the feefor the advisor(s). The M&A fee calculation module 20 may use a look-uptable to estimate the fee. FIG. 3 is a sample look-up table. The tablecan be specific to a particular region or country, such as NorthAmerica, Europe, Germany, etc. As can be seen in FIG. 3, the M&A feecalculation module 20 may estimate that a sole advisor earns AA % of thedeal size for deals having a size between $100M and $500M, earns BB %for deals between $500M and $1 B, and so on. For deals between $100M and$500M, multiple advisors would share a fee of GG % of the deal size. Inpopulating the table with the fee percentage values, a linearizationalgorithm may be applied between two consecutive size groups (e.g.,buckets) to ensure that the estimated fee is a monotone function of thedeal size.

The values of the look-up table may be based on data from previous M&Adeals for which fee percentage allocations are known. For example, whilean investment bank may not know the fee percentages for deals in whichit does not play a role, it typically will have data on the feearrangements for the deals in which it did participate. The values ofthe look-up table may be populated based on that data and any otherreliable data the investment bank may have regarding fee allocations. Insuch cases, the value may be, for example, averages of the feepercentage over a certain time period, such as the previous two years,three years, five years, etc.

Referring back to FIG. 2, at step 40, the M&A fee calculation module 20may aggregate the fee estimation data in order that it may be analyzed.The data may be aggregated in any number of ways to, for example, detectand/or analyze trends in fees, trends in wallet share among investmentbanks, etc. The particular manner in which the data is aggregated may bebased on input from a user of the system 10, received, for example, viaone of the input devices or any other mechanism for providing userinstructions to the system 10. For example, referring to FIG. 4, theestimated M&A fee data may be aggregated to determine the wallet sharefor each investment bank by different M&A deal size over a particulartime period. The output of the M&A fee calculation module 20, such asthe chart of FIG. 4, may be communicated to one of the output devicesfor display.

Past M&A deal data may be used to analyze parameters that have asignificant impact on the fee and, according to various embodiments,only those parameters may be selected to be used by the M&A feecalculation module 20 to sort the M&A deal data. That is, for example,only those parameters, such as region or country, deal size and numberof advisors, shown to have a non-insignificant impact on the fee for M&Adeals may be used.

FIG. 5 is a flowchart of the process flow through the equity productsfee calculation module 22 according to various embodiments of thepresent invention. The process starts at step 50, where the equityproducts fee calculation module 22 retrieves the relevant equity-productdeal data from the database 14. At step 52, the equity products feecalculation module 22 may sort the data by region or country, such asU.S., international, etc. At step 54, the equity products feecalculation module 22 may sort the data by sub-product. The sub-productsfor equity-related products may be, for example, IPOs, offerings ofconvertible securities, secondary offerings and block trades ofsecurities.

Next at step 56 the equity products fee calculation module 22 may sortthe data by deal size. The deal size groupings, or buckets, forequity-related products may be, for example:

Bucket 1 <$100 M Bucket 2   $100 M-$250 M Bucket 3   $250 M-$500 MBucket 4   $500 M-$1 B Bucket 5  >$1 B

Next, at step 58, the deal data may be sorted by the number of bookrunners. Then, at step 60, the fee estimates for the syndicate may bedetermined. The equity products fee calculation module 22 may use alook-up table for each combination of region/sub-product to estimate thefee. FIG. 6 is a sample look-up table for the equity products feecalculation module 22 for a particular combination of region andsub-product. As before, the values of the look-up table may be populatedbased on data that may be available about the fee structures for variouscombinations of region and sub-product for equity-related products.

Equity-related product deals typically have a syndicate with about fourtiers: book runner, lead manager, co-lead manager and co-manager. Thefee percentages in the look-up table of FIG. 6 may represent the feeshared among the various tiers. The equity products fee calculationmodule 22 may utilize an additional look-up table (not shown) toestimate the fee allocation among the various tiers of the syndicate.Typically the book runner(s) gets the most, the lead manager the secondmost, the co-lead manager the third most, and the co-manager typicallyreceives the smallest portion. Different sub-products may have differentdistributions among the tiers of the syndicate. For example, offeringsof convertible securities typically allocate a higher percentage fee tobook runners than other equity-related sub-products. Accordingly, theequity products fee calculation module 22 may utilize different feeallocation look-up tables dependent upon the sub-product.

As before, an analysis may be used to select the parameters by which theequity products fee calculation module 22 sorts the deal data. That is,for example, only those parameters, such as region, deal size, number ofbook runners and sub-product, shown to have a non-insignificant impacton the fee for equity-related product deals, may be used.

Referring back to FIG. 5, at step 62, the equity products feecalculation module 22 may aggregate the fee estimation data in orderthat it may be analyzed. The data may be aggregated in any number ofways to, for example, detect and/or analyze trends in fees, trends inwallet share among investment banks, etc. The particular manner in whichthe data is aggregated may be based on input from a user of the system10, received, for example, via one of the input devices or any othermechanism for providing user instruction to the system 10. For example,referring to FIG. 7, the estimated fee data may be aggregated todetermine wallet share for each investment bank by different deal sizeover a particular time period. The output of the equity products feecalculation module 22 may be communicated to one of the output devicesfor display.

FIG. 8 is a flowchart of the process flow through the investment-gradedebt fee calculation module 24 according to various embodiments of thepresent invention. The process starts at step 70, where theinvestment-grade debt fee calculation module 24 retrieves the relevantinvestment-grade debt deal data from the database 14. At step 72, theinvestment-grade debt fee calculation module 24 may sort the data byregion, such as domestic or international. Because history has shownthat the fees for the various tiers of the book running syndicate forinvestment-grade debt offerings are dependent upon different factors fordomestic (U.S.) and international (non-U.S.) offerings, the feeestimates determined by the investment-grade debt fee calculation module24 may be based on different factors for domestic and internationalofferings, respectively.

Thus, at decision step 74, if it is determined that the offerings aredomestic, the process may advance to step 76, where the investment-gradedebt fee calculation module 24 may sort the domestic investment-gradedebt offering data by sub-product. The sub-products for investment-gradedebt products may be, for example, dollar global bonds, dollarnon-global bonds and retail issuances. Next, at step 78, theinvestment-grade debt fee calculation module 24 may sort the data bymaturity date. The maturity date groupings, or buckets, forinvestment-grade debt products may be, for example:

Bucket 1 18 mos-2 yrs Bucket 2 3-5 yrs Bucket 3 5-6 yrs Bucket 4 7-10yrs Bucket 5 11-15 yrs Bucket 6 15-30 yrs Bucket 7 >30 yrs

Next, at step 80, the fee estimates for the syndicate may be determined.The investment-grade debt fee calculation module 24 may use a look-uptable based on the sub-product to estimate the fee. FIG. 9 is a samplelook-up table for the investment-grade debt fee calculation module 24for a region (such as the U.S.) where a sub-product is a key factor inestimating the fee for investment-grade debt products. As before, thevalues of the look-up table may be populated based on data that may beavailable about the fee structures for various combinations of regionand sub-product for investment-grade debt products.

At step 82, the investment-grade debt fee calculation module 24 mayaggregate the fee estimation data in order that it may be analyzed. Thedata may be aggregated in any number of ways to, for example, detectand/or analyze trends in fees, trends in wallet share among investmentbanks by product, by client, by sector and by region, etc. Theparticular manner in which the data is aggregated may be based on inputfrom a user of the system 10, received, for example, via one of theinput devices or any other mechanism for providing user instruction tothe system 10. The output of the investment-grade debt fee calculationmodule 24 may be communicated to one of the output devices for display.

Returning to step 74, if it is determined that the investment-grade debtofferings are international, the process may advance to step 84, wherethe investment-grade debt fee calculation module 24 may sort theinternational investment-grade debt offering data by credit rating. Thecredit rating groupings for investment-grade debt may be, for example,AAA, AA, A, BBB+, BBB and BBB−. Next, at step 86, the investment-gradedebt fee calculation module 24 may sort the data by maturity date. Thematurity date groupings, or buckets, for investment-grade debt productsmay be the same as for the offerings sorted by sub-product at step 78,or it may be different. For example, according to one embodiment, thematurity date groupings for international investment-grade debtofferings may be:

Bucket 1 3-5 yrs Bucket 2 5-6 yrs Bucket 3 7-10 yrs Bucket 4 11-15 yrsBucket 5 15-30 yrs Bucket 6 >30 yrs

Next, at step 88, the fee estimates for the syndicate may be determined.The investment-grade debt fee calculation module 24 may use a look-uptable based on the credit rating to estimate the fee for such offerings.FIG. 10 is a sample look-up table for the investment-grade debt feecalculation module 24 for a region (such as international offerings)where the credit rating is a key factor in estimating the fee forinvestment-grade debt products. As before, the values of the look-uptable may be populated based on data that may be available about the feestructures for various combinations of region and credit ratings forinvestment-grade debt products. The roles of advisors for investmentgrade debt may be the same as for equity-related products. At step 90,the investment-grade debt fee calculation module 24 may aggregate thefee estimation data in order that it may be analyzed.

As mentioned above, the investment-grade debt fee calculation module 24may use different look-up tables to estimate the advisor fees based onwhether the offerings are domestic or international. This is because, asmentioned above, history has shown that investment-grade debtsub-product is a more significant fee differentiator for domesticofferings and that the credit rating is a more significant feedifferentiator for international offerings. These determinations may bemade, for example, based on an analysis of various factors impacting theadvisor fees with different roles for investment-grade debt offerings.Moreover, the analysis may be performed periodically to assess whetherthe fee assumptions are still valid and, if not, the process flow of theinvestment-grade debt fee calculation module 24 could be correspondinglymodified. That is, for example, if the sub-product no longer becomes asignificant fee differentiator for domestic investment-grade debtofferings, and instead, a key differentiator becomes the credit rating,the process flow of the investment-grade debt fee calculation module 24may be modified to sort all investment-grade debt offerings by creditrating. In such an embodiment, the investment-grade debt fee calculationmodule 24 may still utilize different fee look up tables based on regionif such a distinction is determined to be appropriate. Similarly, if thecredit rating no longer was a significant fee differentiator for aninternational investment-grade debt offering, and instead the keydifferentiator became the sub-product, the process flow of theinvestment-grade debt fee calculation module 24 may be modified to sortall investment-grade debt offerings by sub-product.

In addition, according to various embodiments, if analysis showed thatboth the sub-product and the credit rating were significant factors, theinvestment-grade debt fee calculation module 24 may use, for example,different look-up tables based on various combinations of sub-productand credit rating. Further, in the above example, only two regions wereconsidered: domestic and international. In other embodiments, differingregions could be utilized, such as, for example, North America, Europe,Latin America, Asia, etc. The investment-grade debt fee calculationmodule 24 may estimate the book running fees in such embodiments using,for example, only those factors (e.g., sub-product and/or credit rating)that are significant to the fee in the respective regions.

FIG. 11 is a flowchart of the process flow through the high yield feecalculation module 26 according to various embodiments. The processcommences at step 100, where the data regarding offerings of high-yieldsecurities (e.g., stocks or bonds) are retrieved from the database 14.At step 102, the data may be sorted by, for example, deal size. The dealsize groupings, or buckets, may be, for example, as follows:

Large >$1 B Medium $250 M-$1 B Small <$250 M

Next, at step 104, the data may be sorted by deal year. Next, at step106, the data may be sorted by the role of the advisor in the syndicate,e.g., book runner and non-book runner. At step 108, the high yield feecalculation module 26 may determine the fee estimates based on, forexample, look-up tables based on the role of the advisor. FIGS. 12 and13 are sample look-up tables. FIG. 12 is a sample look-up table for thefee estimate for book runners and FIG. 13 is a sample look-up table forthe fee estimate for non-book runners. Returning to FIG. 11, at step110, the high yield fee calculation module 26 may aggregate the feeestimation data in order that it may be analyzed, as described above.

In the exemplary fee look-up tables of FIGS. 3, 6, 9, 10, 12 and 13, thevalues of the tables are populated with percentages based on pastexperience. Further, as mentioned above, the percentages may belinearized such that the estimated fee is a monotone function. Accordingto other embodiments, the values of the tables may comprise, forexample, equations or numerical models, rather than absolutepercentages, that yield the fee percentage. The equations and/or modelsmay be generated based on, for example, a regression analysis thatgenerates the values of parameters for the equation/model to cause theequation/model to best fit a set of data observations based on pastrelevant deals.

The wallet share determination module 28 may track, for example, walletshare information for the advisors/investment banks based on the feeinformation determined by the modules 20-26. For example, the walletshare determination module 28 may determine a particularadvisor/investment bank's wallet share over a particular time period forM&A deals, equity product deals, investment-grade debt deals and highyield deals. In addition, the wallet share determination module 28 mayperform comparisons of the wallet share of different advisors/investmentbanks for any group of clients, for example, a sector, a country or aregion.

According to various embodiments, the wallet share determination module28 may generate a graphical display such as shown in FIG. 14 toillustrate a comparison between the wallet shares of investment banksfor such types of deals. The wallet share information may span aspecific time period input by the user. The display generated by thewallet share determination module 28 may be displayed on one of theoutput devices, for example. As can be seen in FIG. 14, the display mayinclude a two-dimensional grid. One axis of the grid (e.g., the x-axis)may correspond to the “footprint” for the advisor/investment bank, i.e.,the number of different clients serviced by the advisor/investment bank.A second axis (e.g., the y-axis) may correspond to the wallet share forthe respective client base. A marker having a geometric shape, such as acircle, may be placed at the coordinate of the grid where the footprintof a particular advisor/investment bank meets the wallet sharepercentage for that particular advisor/investment bank. Further, aparameter, such as size, of the marker (such as the radius of a circle)may be indicative or otherwise related to the size of the wallet for theparticular investment bank.

For instance, with reference to the example of FIG. 14, investment bank#1 serviced approximately 150 clients and earned a wallet share ofapproximately 18% from those clients. In contrast, investment bank #2serviced approximately 100 clients and earned a wallet share ofapproximately 16% from those clients. Also, as can be seen from FIG. 14,the wallet size for investment bank #1 is larger (approximately 60%larger) than the wallet share for investment bank #2 because thegeometric shape for investment bank #1 is correspondingly larger thanthe geometric shape for investment bank #2.

While several embodiments of the invention have been described, itshould be apparent, however, that various modifications, alterations andadaptations to those embodiments may occur to persons skilled in the artwith the attainment of some or all of the advantages of the presentinvention. For example, the steps described above in connection withprocess flows of the various modules may be performed in various orders.It is therefore intended to cover all such modifications, alterationsand adaptations without departing from the scope and spirit of thepresent invention as defined by the appended claims.

1. A method of estimating a wallet share for one or more advisors forinvestment banking deals involving investment-grade debt offerings thatoccurred during an evaluation time period, the method comprising:storing, in a database of a computer system, data regarding the dealsinvestment-grade debt offerings during the evaluation time period,wherein the data includes an identification of the one or more advisorsfor each of the deals investment-wade debt offerings during theevaluation time period, the role of the one or more advisors in theinvestment-grade debt offerings during the evaluation time period, and aplurality of parameters for the investment-grade debt offerings, whereinthe plurality of parameters comprise: a maturity of the investment-gradedebt offerings; a credit rating for the investment-grade debt offerings;a geographic region for the investment-made debt offerings; determining,by the computer system, a fee estimate for the one or more advisors forthe investment-grade debt offerings during the evaluation time period,wherein the fee estimate for each investment-grade debt offering isdetermined by determining the geographic region for eachinvestment-grade debt offering; for investment-grade debt offering thatoccurred in a first geographic region, determining the estimates for theone or more advisors based on a first set of parameters using a firstlook-up table for the first geographic region; and for investment-gradedebt offerings that occurred in a second geographic region that isdifferent from the first geographic region, determining the estimatesfor the one or more advisors based on a second set of parameters that isdifferent from the first set of parameters using a second look-up tablefor the second geographic region; and determining, by the computersystem, a wallet share for the one or more advisors over the evaluationtime period based on an aggregation of the fee estimates for the one ormore advisors during the evaluation time period, wherein the computersystem comprises a processor and a computer-readable medium that storesinstructions that are executed by the processor.
 2. The method of claim1, wherein the fee estimate of the first look-up table includes feepercentages.
 3. The method of claim 1, wherein the value of the firstlook-up table includes numerical models.
 4. The method of claim 1,wherein the advisors include at least of a one book runner, a leadmanager, a co-lead manager and a co-manager.
 5. The method of claim 1,further comprising generating values of the first look-up table based onpast information regarding fee allocations for advisors.
 6. The methodof claim 1, further comprising grouping the deals by deal size, andwherein determining the wallet share comprises determining the walletshare by deal size for the one or more advisors.
 7. The method of claim1, wherein: the first set of parameters comprises: the role of the oneor more advisors; the maturity for the investment-grade debt offerings;and a sub-product for the investment-grade debt offerings; and thesecond set of parameters comprises: the role of the one or moreadvisors; the maturity for the investment-grade debt offerings; and thecredit rating for the investment-grade debt offerings.
 8. The method ofclaim 7, wherein the first geographic region is the U.S. and the secondgeographic region is not the U.S.
 9. A computer system for estimating awallet share for one or more advisors for investment banking dealsinvolving investment-grade debt offerings that occurred during anevaluation time period, the computer system comprising: a database thatstores data regarding the investment-grade debt offerings during theevaluation time period, wherein the data includes an identification ofthe one or more advisors for each of the investment-grade debt offeringsduring the evaluation time period, the role of the one or more advisorsin the investment-grade debt offerings during the evaluation timeperiod, and a plurality of parameters for the investment-grade debtofferings, wherein the plurality of parameters comprise: a maturity ofthe investment-grade debt offerings; a credit rating for theinvestment-grade debt offerings; a geographic region for theinvestment-grade debt offerings; a processor in communication with thedatabase; and a memory in communication with the processor, wherein thememory stores instructions that when executed by the processor cause theprocessor to estimate the wallet share for the one or more advisors by:determining a fee estimate for the one or more advisors forinvestment-grade debt offerings during the evaluation time period by:determining the geographic region for each investment-grade debtoffering; for investment-grade debt offering that occurred in a firstgeographic region, determining the estimates for the one or moreadvisors based on a first set of parameters using a first look-up tablefor the first geographic region; and for investment-grade debt offeringsthat occurred in a second geographic region that is different from thefirst geographic region, determining the estimates for the one or moreadvisors based on a second set of parameters using a second look-uptable for the second geographic region, wherein the first set ofparameters are different from the second set of parameters; anddetermining the wallet share for the one or more advisors over theevaluation time period based on an aggregation of the fee estimates forthe one or more advisors during the evaluation time period.
 10. Thecomputer system of claim 9, wherein: the first set of parameterscomprises: the role of the one or more advisors; the maturity for theinvestment-grade debt offerings; and a sub-product for theinvestment-grade debt offerings; and the second set of parameterscomprises: the role of the one or more advisors; the maturity for theinvestment-grade debt offerings; and the credit rating for theinvestment-grade debt offerings.